Suppr超能文献

通过联合方法筛选有前景的喹啉类抗癌药物的决策制定

Decision making for promising quinoline-based anticancer agents through combined methodology.

作者信息

Özcan Evrencan, Ökten Salih, Eren Tamer

机构信息

Department of Industrial Engineering, Faculty of Engineering, Kırıkkale University, Yahşihan, Kırıkkale, Turkey.

Division of Science Education, Department of Mathematics and Science Education, Faculty of Education, Kırıkkale University, Yahşihan, Kırıkkale, Turkey.

出版信息

J Biochem Mol Toxicol. 2020 Sep;34(9):e22522. doi: 10.1002/jbt.22522. Epub 2020 May 14.

Abstract

During the development of effective drugs for the treatment of cancer, one of the most important tasks is to identify effective drug candidates having maximum antiproliferation and minimum side effects. This paper considers the problem of selecting the most promising anticancer agents, showing inhibition at low IC concentration and low releasing lactate dehydrogenase percentage (cytotoxicity). Recently, we prepared quinoline analogs bearing different functional groups and determined their anticancer potential against the HeLa, C6, and HT29 cancer cell lines using different anticancer assays. Experimentally, seven quinoline derivatives consisting of different substituents were determined as promising anticancer agents. We propose a multicriteria recommendation method to identify the most promising anticancer agents against all tested cell lines with an accurate prediction algorithm according to the available input data. A multicriteria decision-making methodology (MCDM) was used for the solution of the relevant problem in this study. Both the experimental results and MCDM method indicated that 5,7-dibromo-8-hydroxyquinoline (2) and 6,8-dibromo-1,2,3,4-tetrahydroquinoline (6) are the most promising anticancer agents against the HeLa, HT29, and C6 cell lines.

摘要

在开发治疗癌症的有效药物过程中,最重要的任务之一是确定具有最大抗增殖作用和最小副作用的有效候选药物。本文考虑了选择最有前景的抗癌药物的问题,这些药物在低IC浓度下具有抑制作用且乳酸脱氢酶释放百分比低(细胞毒性)。最近,我们制备了带有不同官能团的喹啉类似物,并使用不同的抗癌试验测定了它们对HeLa、C6和HT29癌细胞系的抗癌潜力。通过实验,确定了七种由不同取代基组成的喹啉衍生物为有前景的抗癌药物。我们提出了一种多标准推荐方法,根据可用的输入数据,用精确的预测算法来确定针对所有测试细胞系的最有前景的抗癌药物。本研究使用多标准决策方法(MCDM)来解决相关问题。实验结果和MCDM方法均表明,5,7-二溴-8-羟基喹啉(2)和6,8-二溴-1,2,3,4-四氢喹啉(6)是针对HeLa、HT29和C6细胞系最有前景的抗癌药物。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验